It is known to use a “scaler” to increase/decrease the size of a video image by changing a corresponding video signal (formatted for either interlaced or progressive scanning) to provide a scaled video signal that will generate a correspondingly sized (larger/smaller) video image. In contrast, as known by those skilled in the art, a scaler is different from a “deinterlacer” that may change an interlaced formatted video signal to a progressive formatted video signal.
For example, when a video signal of an image is displayed at a 640×480 resolution on a 14-inch monitor, the image may appear relatively clear. However, if the same video signal is provided (at the same resolution) to a 40-inch monitor, the image may be less clear. This situation is caused because the data included in the video signal is spaced apart more on the 40 inch monitor than on the 14 inch monitor.
It is known to create additional data (not included in the original video signal) to be added to the original video signal for display on a higher resolution monitor. The additional data can be created by a process that is referred to as “interpolation” As is known by those skilled in the art, interpolation can be used to create additional data (i.e., interpolated data) that is included between two adjacent pieces of known data. For example, a relatively clear image may be provided to the above 40 inch monitor by creating interpolated data for display when the image size is scaled from 640×480 to 1600×1200. In other words, the number of vertical lines in the displayed image is increased from 480 to 1200 when scaling the image to the 40 inch monitor. Accordingly, the interpolated data can be provided as the pixels which would otherwise be missing from a line of the display if only the original 480 pixels were displayed on the 40 inch monitor.
Linear interpolation using a scaler is discussed, for example, in U.S. Pat. No. 5,793,379, entitled Method and apparatus for scaling images having a plurality of scan lines of pixel data, to Lapidous. As discussed in Lapidous, interpolation data is obtained by filtering existing pixel data using a linear low-pass filter (LPF), weighting the LPF-filtered pixel data, and averaging the result. Additionally, interpolation data, which is close to actual data, can be provided by performing interpolation using a polynomial as discussed, for example, in Multirate Digital Filters, Filter Banks, Polyphase Networks, and Applications by Vaidyanathan, a collection of international learned papers, proc. IEEE, vol. 78, January 1990.